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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1980

A compensation mechanism for central Pacific

Geos 3 derived geoid heights and sea floor topography were averaged into 256 square areas (203 km on a side) for a region in the central Pacific containing a large portion of the Hawaiian Island chain. The whole region is about 500 m shallower than normal sea floor of the same age. The major portion of the depth anomaly is the Hawaiian swell. Data were analyzed using a two-dimensional fast Fourier transform. A transfer function was computed to determine the part of the observed geoid height that is coherent and in phase with the topography. Two models were introduced, one compensating short-wavelength topography at a shallow depth (14 km) and the other compensating the longer wavelengths by a deep mechanism. Using the transition wavelength between the two models (1100 km), an estimate is made of the amplitude and shape of the heat anomaly needed to uplift the Hawaiian swell. The peak of the anomaly has an amplitude of 530 mW/sq m and is located 275 km east of Hawaii.

Sandwell, D. T.↗
NASA NTRS1988

Neutral atomic carbon in dense molecular clouds

The 370 micron 3P2-3P1 fine-structure line of neutral carbon was detected in seven sources: OMC 1, NGC 2024, S140, W3, DR 21, M17, and W51. Simultaneous analysis of J = 2-1 data and available observations of the J = 1-0 line make it possible to deduce optical depths and excitation temperatures for these lines. These data indicate that both C I lines are likely to be optically thin, and that the ratio of C I to CO column densities in these clouds is typically about 0.1.

Zmuidzinas, J.↗
DOE OSTI2021

Hydraulically‐vulnerable trees survive on deep‐water access during droughts in a tropical forest

Summary Deep‐water access is arguably the most effective, but under‐studied, mechanism that plants employ to survive during drought. Vulnerability to embolism and hydraulic safety margins can predict mortality risk at given levels of dehydration, but deep‐water access may delay plant dehydration. Here, we tested the role of deep‐water access in enabling survival within a diverse tropical forest community in Panama using a novel data‐model approach. We inversely estimated the effective rooting depth (ERD, as the average depth of water extraction), for 29 canopy species by linking diameter growth dynamics (1990–2015) to vapor pressure deficit, water potentials in the whole‐soil column, and leaf hydraulic vulnerability curves. We validated ERD estimates against existing isotopic data of potential water‐access depths. Across species, deeper ERD was associated with higher maximum stem hydraulic conductivity, greater vulnerability to xylem embolism, narrower safety margins, and lower mortality rates during extreme droughts over 35 years (1981–2015) among evergreen species. Species exposure to water stress declined with deeper ERD indicating that trees compensate for water stress‐related mortality risk through deep‐water access. The role of deep‐water access in mitigating mortality of hydraulically‐vulnerable trees has important implications for our predictive understanding of forest dynamics under current and future climates.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Pinatubo and pre-Pinatubo optical-depth spectra: Mauna Loa measurements, comparisons, inferred particle size distributions, radiative effects, and relationship to lidar data

The Ames airborne tracking sunphotometer was operated at the National Oceanic and Atmospheric Administration (NOAA) Mauna Loa Observatory (MLO) in 1991 and 1992 along with the NOAA Climate Monitoring and Diagnostics Laboratory (CMDL) automated tracking sunphotometer and lidar. June 1991 measurements provided calibrations, optical-depth spectra, and intercomparisons under relatively clean conditions; later measurements provided spectra and comparisons for the Pinatubo cloud plus calibration checks. June 1991 results are similar to previous MLO springtime measurements, with midvisible particle optical depth at the near-background level of 0.012 +/- 0.006 and no significant wavelength dependence in the measured range (lambda = 0.38 to 1.06 micrometers). The arrival of the Pinatubo cloud in July 1991 increased midvisible particle optical depth by more than an order of magnitude and changed the spectral shape of to an approximate power law with an exponent of about -1.4. By clearly September 1991, the spectrum was broadly peaked near 0.5 micrometers, and by July 1992, it was peaked near 0.8 micrometers. Our optical-depth spectra include corrections for diffuse light. NOAA- and Ames Research Center (ARC)-measured spectra are in good agreement. Columnar size distributions inverted from the spectra show that the initial (July 1991) post-Pinatubo cloud was relatively rich in small particles (r less than 0.25 micrometers), which were progressively depleted in the August-September 1991 and July 1992 periods. Conversely, both of the later periods had more of the optically efficient medium-sized particles (0.25 less than r less than 1 micrometers) than did the fresh July 1991 cloud. These changes are consistent with particle growth by condensation and coagulation. Photometer-inferred column backscatter values agree with those measured by the CMDL lidar on nearby nights. Combining lidar-measured backscatter profiles with photometer-derived backscatter-to-area ratios gives peak particle areas that could cause rapid heterogeneous loss of ozone, given sufficiently low particle acidity and suitable solar zenith angles (achieved at mid- to high latitudes). Top-of-troposphere radiative forcings for the September 1991 and July 1992 optical depths and size distributions over MLO are about -5 and -3 W/sq m, respectively (hence comparable in magnitude but opposite in sign to the radiative forcing caused by the increase in manmade greenhouse gases since the industrial revolution). Heating rates in the Pinatubo layer over MLO are 0.55 +/- 0.13 and 0.41 +/- 0.14 K/d for September 1991 and July 1992, respectively.

Russell, P. B.↗
NASA NTRS1993

Pinatubo and Pre-Pinatubo Optical-Depth Spectra: Mauna Loa Measurements, Comparisons, Inferred Particle Size Distributions, Radiative Effects, and Relationship to Lidar Data

The Ames airborne tracking sunphotometer was operated at the National Oceanic and Atmospheric Administration (NOAA) Mauna Loa Observatory (MLO) in 1991 and 1992 along with the NOAA Climate Monitoring and Diagnostics Laboratory (CMDL) automated tracking sunphotometer and lidar. June 1991 measurements provided calibrations, optical-depth spectra, and intercomparisons under relatively clean conditions; later measurements provided spectra and comparisons for the Pinatubo cloud plus calibration checks. June 1991 results are similar to previous MLO springtime measurements, with midvisible particle optical depth tau(sub p)(lambda = 0.526 microns) at the near-background level of 0.012 +/- 0.006 and no significant wavelength dependence in the measured range (lambda = 0.38 to 1.06 microns). The arrival of the Pinatubo cloud in July 1991 increased midvisible particle optical depth by more than an order of magnitude and changed the spectral shape of tau(sub p)(lambda) to an approximate power law with an exponent of about -1.4. By early September 1991, the spectrum was broadly peaked near 0.5 microns, and by July 1992, it was peaked near 0.8 microns. Our optical-depth spectra include corrections for diffuse light which increase postvolcanic midvisible tau(sub p) values by 1 to 3% (i.e., 0.0015 to 0.0023). NOAA- and Ames Research Center (ARC)-measured spectra are in good agreement. Columnar size distributions inverted from the spectra show that the initial (July 1991) post-Pinatubo cloud was relatively rich in small particles (r less than 0.25 microns), which were progressively depleted in the August-September 1991 and July 1992 periods. Conversely, both of the later periods had more of the optically efficient medium-sized particles (0.25 less than r less than 1 micron) than did the fresh July 1991 cloud. These changes are consistent with particle growth by condensation and coagulation. The effective, or area-weighted, radius increased from 0.22 +/- 0.06 micron in July 1991 to 0.56 +/- 0.12 micron in August-September 1991 and to 0.86 +/- 0.29 micron in July 1992. Corresponding column mass values were 4.8 +/- 0.7, 9.1 +/- 2.7, and 5.5 +/- 2 micro g/sq cm, and corresponding column surface areas were 4.4 +/- 0.5, 2.9 +/- 0.2, and 1.1 +/- 0.1 sq micron/sq cm,. Photometer-inferred column backscatter values agree with those measured by the CMDL lidar on nearby nights. Combining lidar-measured backscatter profiles with photometer-derived backscatter-to-area ratios gives peak particle areas that could cause rapid heterogeneous loss of ozone, given sufficiently low particle acidity and suitable solar zenith angles (achieved at mid- to high latitudes). Top-of-troposphere radiative forcings for the September 1991 and July 1992 optical depths and size distributions over MLO are about -5 and -3 W 1/sq m, respectively (hence comparable in magnitude but opposite in sign to the radiative forcing caused by the increase in manmade greenhouse gases since the industrial revolution). Heating rates in Pinatubo layer over MLO are 0.55 +/- 0.13 and 0.41 +/- 0.14 K/d for September 1991 and July 1992, respectively.

Russell, P. B.↗
NASA NTRS2013

The MJO Transition from Shallow to Deep Convection in CloudSat/CALIPSO Data and GISS GCM Simulations

The relationship between convective penetration depth and tropospheric humidity is central to recent theories of the Madden-Julian oscillation (MJO). It has been suggested that general circulation models (GCMs) poorly simulate the MJO because they fail to gradually moisten the troposphere by shallow convection and simulate a slow transition to deep convection. CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are analyzed to document the variability of convection depth and its relation to water vapor during the MJO transition from shallow to deep convection and to constrain GCM cumulus parameterizations. Composites of cloud occurrence for 10MJO events show the following anticipatedMJO cloud structure: shallow and congestus clouds in advance of the peak, deep clouds near the peak, and upper-level anvils after the peak. Cirrus clouds are also frequent in advance of the peak. The Advanced Microwave Scanning Radiometer for EarthObserving System (EOS) (AMSR-E) columnwater vapor (CWV) increases by;5 mmduring the shallow- deep transition phase, consistent with the idea of moisture preconditioning. Echo-top height of clouds rooted in the boundary layer increases sharply with CWV, with large variability in depth when CWV is between;46 and 68 mm. International Satellite Cloud Climatology Project cloud classifications reproduce these climatological relationships but correctly identify congestus-dominated scenes only about half the time. A version of the Goddard Institute for Space Studies Model E2 (GISS-E2) GCM with strengthened entrainment and rain evaporation that produces MJO-like variability also reproduces the shallow-deep convection transition, including the large variability of cloud-top height at intermediate CWV values. The variability is due to small grid-scale relative humidity and lapse rate anomalies for similar values of CWV. 1.

DelGenio, Anthony G.↗
DOE OSTI2024

Groundwater and Surface Water Flow (GSFLOW) model files to explore bedrock circulation depth and porosity in Copper Creek, Colorado

This data package contains integrated hydrological model input and output files for Copper Creek, Colorado (24 km2), a tributary of the East River located in the headwaters of the Upper Colorado River Basin. The model code is the U.S. Geological Survey (USGS) Groundwater and Surface Water Flow (GSFLOW) model. The model contains a 100-m grid resolution and a daily timestep. The land surface model is dynamically linked to a three-dimensional groundwater flow model that allows for streamflow gaining and losing conditions. The groundwater model contains 12 model layers and extends 400 m below land surface. The original Copper Creek model was modified to contain geologic layers representing saprolite, shallow bedrock, and deep bedrock. Endmember depth versus hydraulic conductivity relationships and porosity values for fractured crystalline rock are simulated. For the shallow case, median flow depths occur in the shallow saprolite at depths <8 m, while the deep case promotes a median groundwater flow depth of 100 m. With this modeling framework we compare streamflow response to a plausible worst-case drought lasting up to five years. Streamflow metrics of analysis include average streamflow, fraction of stream network that is dry, no-flow duration, average groundwater flow to streams and time to recovery following the drought. Results and implications are presented in a paper submitted to Geophysical Research Letters titled, "The role of bedrock circulation depth and porosity in mountain streamflow response to prolonged drought" by Rosemary WH. Carroll, Andrew H. Manning and Kenneth H Williams. A Readme.txt file provides instructions on how to download all model files and execute each model scenario. In addition to the GSFLOW output/prms/copper_drought.csv file containing daily basin water stores and fluxes (refer to GSFLOW manual) and the output/prms/copper_drought_statvar.dat file with output defined in the gsflow3.control file (refer to GSFLOW Manual), output files also include spatially distributed daily values of total evapotranspiration, canopy evaporation, precipitation, snowfall, infiltration, snow water equivalent, potential evapotranspiration, recharge, sublimation, soil moisture, contributing interflow, water table elevations, changes in groundwater storage, groundwater evapotranspiration, interbasin groundwater flow (limited to the alluvium below the stream outlet), and surface-groundwater exchanges within the river system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Discovering Geothermal Systems in the Great Basin Region: An Integrated Geologic, Geochemical, and Geophysical Approach for Establishing Geothermal Play Fairways

The Great Basin currently hosts ~24 geothermal power plants with more than 600 MW of capacity, but estimates suggest that the region is capable of producing much greater amounts of geothermal energy. Recent studies indicate that a combination of geological, geochemical, and geophysical features characterize the most robust geothermal systems. Considering that most of the geothermal resources in this region are blind, it is imperative that the favorable characteristics for geothermal activity be synthesized and techniques perfected for the discovery of new viable systems. We therefore utilized a multi-disciplinary approach and synthesized 9 geologic, geochemical, and geophysical parameters to produce a new detailed geothermal play fairway map of a large transect across the Great Basin region (96,000 km2) from west-central to eastern Nevada, with the primary objective of facilitating discovery of commercial-grade, blind geothermal fields (i.e. systems with no surface hot springs or fumaroles). Our analysis included: 1) structural settings (i.e., patterns of faulting), 2) age of recent faulting, 3) slip rates on recent faults, 4) regional-scale strain rates, 5) the tendency of faults to slip or dilate based on their orientation in the regional stress field, 6) earthquake density, 7) gravity data, 8) temperature at 3 km depth, and 9) geochemistry from springs and wells. These parameters were grouped into subsets to delineate rankings for local permeability, regional permeability, and heat, which collectively defined the geothermal play fairways (i.e., most likely locations for significant geothermal fluid flow). A major challenge was developing appropriate weightings of individual data types to best predict permeability and overall geothermal potential. Rigorous statistical methods, utilizing 34 benchmarks of known relatively high-temperature (>130°C) geothermal systems in the region, were employed to determine the hierarchal weights of each parameter. The new geothermal potential maps will help to reduce the risks in prospecting for new geothermal systems throughout the region.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Multiscale maps of Active Layer Depth for Teller site Mile Marker 27 and Kougarok Mile Marker 80, Seward Peninsula, AK

Remote sensing maps of active layer depth derived from Unmanned Areal System (UAS) data. The UAS datasets were stepwise scaled until matching the AVIRIS-NG (Airborne Visible / Infrared Imaging Spectrometer - Next Generation) and Sentinel-2 spatial resolutions. Using the field observed Active Layer Depth (ALD) measurement in combination with spectral and topographic predictors derivatives from DJI UAS imagery, we used a spatially explicit RF regression model to predict and map ALD across our study landscapes. This package includes maps for Next-Generation Ecosystem Experiment Arctic (NGEE Arctic)’s Teller Mile Marker (MM) 27, and Kougarok MM80 (aka Mile 80) watersheds. The field, map data, and metadata are provided as geoTIF and text (*.csv) formats. These datasets are provided in support of Hantson et al., 2024 (accepted) “Scaling Arctic landscape and permafrost features improves active layer depth modeling”

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Transitioning the California Energy Commission Eligible Equipment List to a National Platform

The Energy Commission called on the National Renewable Energy Laboratory's (NREL)'s Solar Technical Assistance Team to explore various pathways for supporting continued evolution of the list. NREL staff utilized the Database of State Incentives for Renewables and Efficiency (DSIRE), California Solar Initiative (CSI) data, and information from in-depth interviews to better understand the impact of a lack of an updated list and suggest potential solutions. A total of 18 people from state energy offices, rebate program administrators, utilities, national testing laboratories, private companies, nonprofit organizations, and the federal government were interviewed between July and September 2013. CSI data were analyzed to illustrate the monetary benefits of the algorithm behind calculating performance of PV modules included on the list. The primary objectives of this study are to: 1) Determine the impact of not maintaining the list, and 2) Explore alternatives to the State of California's maintenance of the list.

14 SOLAR ENERGY↗
DOE OSTI2022

Effects of Cone Penetrometer Testing on Shallow Hydrogeology at a Contaminated Site

Penetration testing is a popular and instantaneous technique for subsurface mapping, contaminant tracking, and the determination of soil characteristics. While the small footprint and reproducibility of cone penetrometer testing makes it an ideal method for in-situ subsurface investigations at contaminated sites, the effects to local shallow groundwater wells and measurable influence on monitoring networks common at contaminated sites is unknown. Physical and geochemical parameters associated with cone penetrometer testing were measured from a transect of shallow groundwater monitoring wells adjacent to penetrometer testing. For wells screened above the depth of cone refusal, the physical advancement and retraction of the cone had a significant effect ( p < 0.01) on water level for several pushes within 10 meters of a monitoring well, and a measured increase in specific conductivity. No effect on geochemistry or water level was observed in continuous monitoring data from wells screened below the depth of cone refusal, but variability in specific conductivity from these wells during penetration testing was only a fraction of the natural variation measured during precipitation events. Continuous measurements of specific conductivity and water level demonstrated that the effects of penetration testing have limited spatial and temporal distributions with a null effect post-testing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Performance of Pulsed Thermal Tomography Imaging with Machine Learning-Based Classification of Defects in Additively Manufactured Structures

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermal Tomography Imaging (PTT) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTT capabilities in detecting and visualizing microscopic defects in metallic specimens. The thermal tomography (TT) algorithm obtains depth reconstructions of spatial effusivity from the data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring of images with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images. CNN is trained on a database of TT images created for a set of simulated metallic structures with elliptical subsurface voids. Test of CNN performance demonstrate the ability to classify radii and angular orientation of subsurface defects in TT images. In addition, we have shown that CNN trained on elliptical defects is capable of classifying irregular-shaped defects obtained from scanning electron microscopy (SEM) of stainless steel sections printed with LPBF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1993

Comparison of cloud microphysical parameters derived from surface and satellite measurements during FIRE phase 2

Cloud microphysical properties are an important component in climate model parameterizations of water transport, cloud radiative exchange, and latent heat processes. Estimation of effective cloud particle size, liquid or ice water content, and optical depth from satellite-based instrumentation is needed to develop a climatology of cloud microphysical properties and to better understand and model cloud processes in atmospheric circulation. These parameters are estimated from two different surface data sets taken at Coffeyville, Kansas, during the First ISCCP Regional Experiment (FIRE) Phase-2 Intensive Field Observation (IFO) period (November 13 - December 7, 1991). Satellite data can also provide information about optical depth and effective particle size. This paper explores the combination of the FIRE-2 surface and satellite data to determine each of the cloud microphysical properties.

Young, David F.↗
DOE OSTI2023

DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection

Abstract Artificial intelligence methods show great promise in increasing the quality and speed of work with large astronomical datasets, but the high complexity of these methods leads to the extraction of dataset-specific, non-robust features. Therefore, such methods do not generalize well across multiple datasets. We present a universal domain adaptation method, DeepAstroUDA , as an approach to overcome this challenge. This algorithm performs semi-supervised domain adaptation (DA) and can be applied to datasets with different data distributions and class overlaps. Non-overlapping classes can be present in any of the two datasets (the labeled source domain, or the unlabeled target domain), and the method can even be used in the presence of unknown classes. We apply our method to three examples of galaxy morphology classification tasks of different complexities (three-class and ten-class problems), with anomaly detection: (1) datasets created after different numbers of observing years from a single survey (Legacy Survey of Space and Time mock data of one and ten years of observations); (2) data from different surveys (Sloan Digital Sky Survey (SDSS) and DECaLS); and (3) data from observing fields with different depths within one survey (wide field and Stripe 82 deep field of SDSS). For the first time, we demonstrate the successful use of DA between very discrepant observational datasets. DeepAstroUDA is capable of bridging the gap between two astronomical surveys, increasing classification accuracy in both domains (up to 40 % on the unlabeled data), and making model performance consistent across datasets. Furthermore, our method also performs well as an anomaly detection algorithm and successfully clusters unknown class samples even in the unlabeled target dataset.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2012

Improved Cloud and Snow Screening in MAIAC Aerosol Retrievals Using Spectral and Spatial Analysis

An improved cloud/snow screening technique in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is described. It is implemented as part of MAIAC aerosol retrievals based on analysis of spectral residuals and spatial variability. Comparisons with AERONET aerosol observations and a large-scale MODIS data analysis show strong suppression of aerosol optical thickness outliers due to unresolved clouds and snow. At the same time, the developed filter does not reduce the aerosol retrieval capability at high 1 km resolution in strongly inhomogeneous environments, such as near centers of the active fires. Despite significant improvement, the optical depth outliers in high spatial resolution data are and will remain the problem to be addressed by the application-dependent specialized filtering techniques.

Lyapustin, A.↗
NASA NTRS1994

Infrared spectroscopy of Seyfert 2 galaxies: A look through the obscuring Torus?

We present both high-resolution (R = 1260) and low-resolution (R = 345 and 425) J-band spectra of a sample of 15 Seyfert 2 galaxies. Our goal is to look for broad Pa beta lines, indicating broad-line regions which are hidden by dust from our view at optical wavelengths. Of the 15 objects studied here, three have broad Pa beta lines: MCG-05.23.16, Mrk 463E, and NGC 2992. Mrk 176 and NGC 5728 may also have weak broad lines. In NGC 5506, previously reported to have broad Pa beta and hydrogen alpha lines, we find that the Pa beta line profile is continuous and has the same shape as the nearby line (Fe II) lambda 1.2567, which should not have a broad component. We interpret these observations as gas from the narrow-line region (NLR) with no broad component. In NGC 5506, however, the NLR profiles become broader with increasing wavelength, indicating that highly reddened wings are becoming more readily visible at the longer wavelengths. We confirm the correlation of (O I) lambda 6300/hydrogen alpha and (Fe II) lambda 1.644/Br gamma (the latter transformed to (Fe II) lambda 1.2567/Pa beta to compare with our data) found by previous authors when comparing active galactic nuclei (AGNs), supernova remnants, starbursts, and H II regions. The correlation confirms that in all of these objects both (O I) lambda 6300 and the (Fe II) lines come from partially ionized regions in which hydrogen is mostly neutral. Comparison of the infrared optical depths with column depths determined from X-ray data show a general tendency for the objects with detected broad Pa beta to have lower X-ray columns.

Goodrich, Robert W.↗
NASA NTRS1993

Evaluation of the Sparton tight-tolerance AXBT

Forty-six near-simultaneous pairs of conductivity - temperature - depth (CTD) and Sparton 'tight tolerance' air expendable bathythermograph (AXBT) temperature profiles were obtained in summer 1991 from a location in the Sargasso Sea. The data were analyzed to assess the temperature and depth accuracies of the Sparton AXBTs. The tight-tolerance criterion was not achieved using the manufacturer's equations but may have been achieved using customized equations computed from the CTD data. The temperature data from the customized equations had a one standard deviation error of 0.13 C. A customized elapsed fall time-to-depth conversion equation was found to be z = 1.620t - 2.2384 x 10(exp -4) t(exp 2) + 1.291 x 10(exp -7) t(exp 3), with z the depth in meters and t the elapsed fall time after probe release in seconds. The standard deviation of the depth error was about 5 m; a rule of thumb for estimating maximum bounds on the depth error below 100 m could be expressed as +/-2% of depth or +/- 10 m, whichever is greater. This equation gave greater depth accuracy than either the manufacturer's supplied equation or the navy standard equation.

Boyd, Janice D.↗
NASA NTRS1992

The remote sensing of ocean primary productivity - Use of a new data compilation to test satellite algorithms

Global pigment and primary productivity algorithms based on a new data compilation of over 12,000 stations occupied mostly in the Northern Hemisphere, from the late 1950s to 1988, were tested. The results showed high variability of the fraction of total pigment contributed by chlorophyll, which is required for subsequent predictions of primary productivity. Two models, which predict pigment concentration normalized to an attenuation length of euphotic depth, were checked against 2,800 vertical profiles of pigments. Phaeopigments consistently showed maxima at about one optical depth below the chlorophyll maxima. CZCS data coincident with the sea truth data were also checked. A regression of satellite-derived pigment vs ship-derived pigment had a coefficient of determination. The satellite underestimated the true pigment concentration in mesotrophic and oligotrophic waters and overestimated the pigment concentration in eutrophic waters. The error in the satellite estimate showed no trends with time between 1978 and 1986.

Balch, William↗